In this thesis, I use bioinformatic approaches to address new and existing issues surrounding large-scale phylogenetic analysis. A phylogenetic analysis pipeline is developed to aid an investigation of the suitability of integrating Cytochrome Oxidase Subunit 1 (cox1) into phylogenetic supermatrices. In the first two chapters I assess the effect of varying cox1 sample size within a large variable phylogenetic context. As well as intuitive results on increased quality with greater taxon sampling, there are clear monophyly patters relating to local taxonomic sampling. Specifically, more monophyletic resampled taxa in cases when fewer consubfamilials are represented, with a tendency for these to remain unchanged in the degree of monophyly when rarefied. Sampling analyses are extended in chapter two using a mined Scarabaeoidea multilocus dataset, where taxa from given loci are used to improve existing matrices. Improvement in phylogenetic signal is best achieved by targeting cox1 to existing taxa, which suggests minimum parameters for cox1 adoption in large-scale phylogenetics. In chapter 3 I address recently-arisen issues related to phyloinformatic analysis of sequence-delineated matrices. There is ongoing work on setting species boundaries by sequence variation alone, but incongruence results in methodological issues upon integrating multiple loci delineated in this way. In the final chapter I assess the impact of heterogeneous substitution rates on large scale cox1 datasets. Although the number of heterogeneous sites in Coleoptera cox1 is substantial, their presence is found to be beneficial, as their removal negatively impacts the ability of the alignment to generate the 'known' topology. The homoplasy and heterogeneous characteristics of cox1 have not substantially impacted its utility, thus the cox1 datasets have potential to play a substantial role in the tree-of-life.